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    <abstract>This paper presents the IBM Research AI submission to the CoNLL 2018 Shared Task on Parsing Universal Dependencies. Our system implements a new joint transition-based parser, based on the Stack-LSTM framework and the Arc-Standard algorithm, that handles tokenization, part-of-speech tagging, morphological tagging and dependency parsing in one single model. By leveraging a combination of character-based modeling of words and recursive composition of partially built linguistic structures we qualified 13th overall and 7th in low resource. We also present a new sentence segmentation neural architecture based on Stack-LSTMs that was the 4th best overall.</abstract>
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%0 Conference Proceedings
%T IBM Research at the CoNLL 2018 Shared Task on Multilingual Parsing
%A Wan, Hui
%A Naseem, Tahira
%A Lee, Young-Suk
%A Castelli, Vittorio
%A Ballesteros, Miguel
%Y Zeman, Daniel
%Y Hajič, Jan
%S Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F wan-etal-2018-ibm
%X This paper presents the IBM Research AI submission to the CoNLL 2018 Shared Task on Parsing Universal Dependencies. Our system implements a new joint transition-based parser, based on the Stack-LSTM framework and the Arc-Standard algorithm, that handles tokenization, part-of-speech tagging, morphological tagging and dependency parsing in one single model. By leveraging a combination of character-based modeling of words and recursive composition of partially built linguistic structures we qualified 13th overall and 7th in low resource. We also present a new sentence segmentation neural architecture based on Stack-LSTMs that was the 4th best overall.
%R 10.18653/v1/K18-2009
%U https://aclanthology.org/K18-2009
%U https://doi.org/10.18653/v1/K18-2009
%P 92-102

Markdown (Informal)

[IBM Research at the CoNLL 2018 Shared Task on Multilingual Parsing](https://aclanthology.org/K18-2009) (Wan et al., CoNLL 2018)

• IBM Research at the CoNLL 2018 Shared Task on Multilingual Parsing (Wan et al., CoNLL 2018)

ACL

• Hui Wan, Tahira Naseem, Young-Suk Lee, Vittorio Castelli, and Miguel Ballesteros. 2018. IBM Research at the CoNLL 2018 Shared Task on Multilingual Parsing. In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 92–102, Brussels, Belgium. Association for Computational Linguistics.